Closed-path Eddy Covariance Research Articles

Aerosol interference with open-path eddy covariance measurement in a lake environment

Open-path eddy covariance (OPEC) is widely used for measuring trace gas fluxes between the surface and the atmosphere. At a lake in Eastern China (Lake Taihu), the CO2 flux measured with OPEC was often negative at night (with values as low as −22.1 μmol m−2 s−1) and was coherent across the whole lake, as if the lake were a large sink of atmospheric CO2. The purpose of this study is to investigate the cause of this negative flux phenomenon. In addition to OPEC, we also used closed-path eddy covariance (CPEC) and the transfer coefficient (TC) method to measure the flux. The results show that the persistent negative CO2 flux phenomenon was observed with OPEC but not with CPEC or TC. Because air drawn into the CPEC analyzer was filtered but the OPEC analyzer was influenced by aerosol contamination, the most logical explanation was that particles deposited on the optical lens of the OPEC analyzer changed its cross-sensitivity to water vapor. The direct evidence of this interference was a strong positive correlation between the OPEC analyzer's signal strength and the CO2 mixing ratio observed at 10 Hz. We suggest that it is possible to perform post-field correction to this negative flux bias using the 10 Hz signal strength data. In comparison, an OPEC system at a nearby land site did not experience aerosol interference due to low water vapor flux at night and lack of hygroscopic growth of particles on the optical lens in low humidity conditions. The type of aerosol interference reported here may also occur in high humidity and high pollution conditions elsewhere.

Variations in CO2 and CH4 Exchange in Response to Multiple Biophysical Factors from a Mangrove Wetland Park in Southeastern China

Mangrove ecosystems can be both significant sources and sinks of greenhouse gases. The restoration of mangrove forests is increasingly used as a natural climate solution tool to mitigate climate change. However, the estimates of carbon exchanges remain unclear, especially from restored mangroves. In this study, we observed the temporal variations in carbon dioxide (CO2) and methane (CH4) fluxes and their biophysical controls for 4 years, based on a closed-path eddy covariance (EC) system. The measurements were conducted in a mangrove wetland park with 14-year-old restored mangroves surrounded by open waters in Guangdong Province, China. The EC measurements showed that the mangrove ecosystem acted as a CO2 source with a net CO2 ecosystem exchange (NEE) of 305 g C m−2 from January 2019 to May 2020 by the 5-m tower measurement. After the tower was adjusted to 10 m, the mangrove showed a CO2 sink with an NEE of −345 g C m−2 from June 2020 to December 2022. The change in tower height influenced the interpretation of interannual trends on NEE. There were no significant interannual trends in the gross primary productivity (GPP) and the ecosystem respiration (Re) values. The change from CO2 source to sink may be attributed to the decrease in land surface proportion by the tower replacement, which reduces the proportion of the mangrove canopy respiration and, therefore, captures lower CO2 fluxes from open waters. The restored mangroves indicated strong CH4 sources of 23.2–26.3 g C m−2 a−1. According to the random forest analysis, the land surface proportion, radiation, and relative humidity were the three most important predictors of NEE, while the CH4 flux was most sensitive to air temperature. Compared to the natural and long-term restored mangroves, this 14-year-old restored mangrove had not yet achieved a maximum carbon sequestration capability. Our study highlights the need for the careful design of long-term observations from restored mangroves and proposes future needs in the context of carbon neutrality.

Methane dynamics from a mixed plantation of north China: Observation using closed-path eddy covariance method.

Although an important greenhouse gas, methane flux in hilly forest ecosystems remains unclear. By using closed-path eddy covariance systems, methane flux was measured continuously from 2017 to 2019 in a mixed plantation in the Xiaolangdi area of the Yellow River in North China. The methane flux footprint and its diurnal and monthly variations were analysed, and its characteristics on rainy days are discussed. The results showed that: (a) the observation data were reliable with good spatial representation (b) The methane flux in the mixed plantation ecosystem had obvious diurnal and seasonal variations: the monthly average diurnal variation of the methane flux had a single-peak; the methane flux value was source in the daytime and sink at night. The daily mean maximum value of methane flux in growing season was lower than that in non-growing season with the maximum value appearing in March, and the minimum value in October. (c) The forest is an atmospheric CH4 source with the annual emission in 2017 of (3.31g C·m-2·year -1) >2019 (2.94g C·m-2·year-1) >2018 (2.81g C·m-2·year -1), and the main influencing factor was precipitation. Rainfall affected CH4 flux with a lag period of approximately three days. Rainfall also changed the balance of CH4 flux between sink or source according to precipitation intensity and frequency.

The effect of relative humidity on eddy covariance latent heat flux measurements and its implication for partitioning into transpiration and evaporation

While the eddy covariance (EC) technique is a well-established method for measuring water fluxes (i.e., evaporation or 'evapotranspiration’, ET), the measurement is susceptible to many uncertainties. One such issue is the potential underestimation of ET when relative humidity (RH) is high (>70%), due to low-pass filtering with some EC systems. Yet, this underestimation for different types of EC systems (e.g. open-path or closed-path sensors) has not been characterized for synthesis datasets such as the widely used FLUXNET2015 dataset. Here, we assess the RH-associated underestimation of latent heat fluxes (LE, or ET) from different EC systems for 163 sites in the FLUXNET2015 dataset. We found that the LE underestimation is most apparent during hours when RH is higher than 70%, predominantly observed at sites using closed-path EC systems, but the extent of the LE underestimation is highly site-specific. We then propose a machine learning based method to correct for this underestimation, and compare it to two energy balance closure based LE correction approaches (Bowen ratio correction, BRC, and attributing all errors to LE). Our correction increases LE by 189% for closed-path sites at high RH (>90%), while BRC increases LE by around 30% for all RH conditions. Additionally, we assess the influence of these corrections on ET-based transpiration (T) estimates using two different ET partitioning methods. Results show opposite responses (increasing vs. slightly decreasing T-to-ET ratios, T/ET) between the two methods when comparing T based on corrected and uncorrected LE. Overall, our results demonstrate the existence of a high RH bias in water fluxes in the FLUXNET2015 dataset and suggest that this bias is a pronounced source of uncertainty in ET measurements to be considered when estimating ecosystem T/ET and WUE.

Accuracies of field CO2–H2O data from open-path eddy-covariance flux systems: assessment based on atmospheric physics and biological environment

Abstract. Ecosystem CO2–H2O data measured by infrared gas analyzers in open-path eddy-covariance (OPEC) systems have numerous applications, such as estimations of CO2 and H2O fluxes in the atmospheric boundary layer. To assess the applicability of the data for these estimations, data uncertainties from analyzer measurements are needed. The uncertainties are sourced from the analyzers in zero drift, gain drift, cross-sensitivity, and precision variability. These four uncertainty sources are individually specified for analyzer performance, but so far no methodology exists yet to combine these individual sources into a composite uncertainty for the specification of an overall accuracy, which is ultimately needed. Using the methodology for closed-path eddy-covariance systems, this overall accuracy for OPEC systems is determined from all individual uncertainties via an accuracy model and further formulated into CO2 and H2O accuracy equations. Based on atmospheric physics and the biological environment, for EC150 infrared CO2–H2O analyzers, these equations are used to evaluate CO2 accuracy (±1.22 mgCO2 m−3, relatively ±0.19 %) and H2O accuracy (±0.10 gH2O m−3, relatively ±0.18 % in saturated air at 35 ∘C and 101.325 kPa). Both accuracies are applied to conceptual models addressing their roles in uncertainty analyses for CO2 and H2O fluxes. For the high-frequency air temperature derived from H2O density along with sonic temperature and atmospheric pressure, the role of H2O accuracy in its uncertainty is similarly addressed. Among the four uncertainty sources, cross-sensitivity and precision variability are minor, although unavoidable, uncertainties, whereas zero drift and gain drift are major uncertainties but are minimizable via corresponding zero and span procedures during field maintenance. The accuracy equations provide rationales to assess and guide the procedures. For the atmospheric background CO2 concentration, CO2 zero and CO2 span procedures can narrow the CO2 accuracy range by 40 %, from ±1.22 to ±0.72 mgCO2 m−3. In hot and humid weather, H2O gain drift potentially adds more to the H2O measurement uncertainty, which requires more attention. If H2O zero and H2O span procedures can be performed practically from 5 to 35 ∘C, the H2O accuracy can be improved by at least 30 %: from ±0.10 to ±0.07 gH2O m−3. Under freezing conditions, the H2O span procedure is impractical but can be neglected because of its trivial contributions to the overall uncertainty. However, the zero procedure for H2O, along with CO2, is imperative as an operational and efficient option under these conditions to minimize H2O measurement uncertainty.

Air temperature equation derived from sonic temperature and water vapor mixing ratio for turbulent airflow sampled through closed-path eddy-covariance flux systems

Abstract. Air temperature (T) plays a fundamental role in many aspects of the flux exchanges between the atmosphere and ecosystems. Additionally, knowing where (in relation to other essential measurements) and at what frequency T must be measured is critical to accurately describing such exchanges. In closed-path eddy-covariance (CPEC) flux systems, T can be computed from the sonic temperature (Ts) and water vapor mixing ratio that are measured by the fast-response sensors of a three-dimensional sonic anemometer and infrared CO2–H2O analyzer, respectively. T is then computed by use of either T=Ts1+0.51q-1, where q is specific humidity, or T=Ts1+0.32e/P-1, where e is water vapor pressure and P is atmospheric pressure. Converting q and e/P into the same water vapor mixing ratio analytically reveals the difference between these two equations. This difference in a CPEC system could reach ±0.18 K, bringing an uncertainty into the accuracy of T from both equations and raising the question of which equation is better. To clarify the uncertainty and to answer this question, the derivation of T equations in terms of Ts and H2O-related variables is thoroughly studied. The two equations above were developed with approximations; therefore, neither of their accuracies was evaluated, nor was the question answered. Based on first principles, this study derives the T equation in terms of Ts and the water vapor molar mixing ratio (χH2O) without any assumption and approximation. Thus, this equation inherently lacks error, and the accuracy in T from this equation (equation-computed T) depends solely on the measurement accuracies of Ts and χH2O. Based on current specifications for Ts and χH2O in the CPEC300 series, and given their maximized measurement uncertainties, the accuracy in equation-computed T is specified within ±1.01 K. This accuracy uncertainty is propagated mainly (±1.00 K) from the uncertainty in Ts measurements and a little (±0.02 K) from the uncertainty in χH2O measurements. An improvement in measurement technologies, particularly for Ts, would be a key to narrowing this accuracy range. Under normal sensor and weather conditions, the specified accuracy range is overestimated, and actual accuracy is better. Equation-computed T has a frequency response equivalent to high-frequency Ts and is insensitive to solar contamination during measurements. Synchronized at a temporal scale of the measurement frequency and matched at a spatial scale of measurement volume with all aerodynamic and thermodynamic variables, this T has advanced merits in boundary-layer meteorology and applied meteorology.

Nitrous oxide flux observed with tall-tower eddy covariance over a heterogeneous rice cultivation landscape

Although croplands are known to be strong sources of anthropogenic N2O, large uncertainties still exist regarding their emission factors, that is, the proportion of N in fertilizer application that escapes to the atmosphere as N2O. In this study, we report the results of an experiment on the N2O flux in a landscape dominated by rice cultivation in the Yangtze River Delta, China. The observation was made with a closed-path eddy covariance system on a 70-m tall tower from October 2018 to December 2020 (27 months). Temperature and precipitation explained 78% of the seasonal and interannual variability in the observed N2O flux. The growing season (May to October) mean flux (1.14 nmol m−2 s−1) was much higher than the median flux found in the literature for rice paddies. The mean N2O flux during the observational period was 0.90 ± 0.71 nmol m−2 s−1, and the annual cumulative N2O emission was 7.6 and 9.1 kg N2O-N ha−1 during 2019 and 2020, respectively. The corresponding landscape emission factor was 3.8% and 4.6%, respectively, which were much higher than the IPCC default direct (0.3%) and indirect emission factors (0.75%) for rice paddies.

Net CO2 and CH4 emissions from restored mangrove wetland: New insights based on a case study in estuary of the Pearl River, China

Mangroves have the potential to affect climate via C sequestration and methane (CH4) emissions. With half of the world's mangroves lost during the 20th century, mangrove restoration in mitigating greenhouse gases has been increasingly recognized. However, the carbon exchanges during restored processes still remain large uncertain. In this study, we analyzed the temporal variations of CO2 and CH4 fluxes and their environmental controls during 2019 and 2020 based on a closed-path eddy covariance (EC) system in a 12-year restored subtropical mangrove wetland, in estuary of the Pearl River, southeastern China. We also estimated the CO2 and CH4 fluxes and their climate effect from the beginning of restoration by Random Forest algorithm (RF). The EC observations showed that annually the 12-year restored mangrove acted as CO2 and CH4 sources, with net CO2 ecosystem exchange (NEE) of 82–175 gC·m- 2·a−1 and CH4 fluxes of 24.7–26.3 gC·m−2·a−1. Low vegetation gross primary productivity (GPP) and high ecosystem respiration (Re) caused net CO2 emissions in the mangroves. The estimation by RF indicated that the mangroves were always a CO2 source after the beginning of restoration, but the annual NEE was linearly decreased from 233 to 131 gC·m−2·a−1 from 2008 to 2020. The annual CH4 emissions continually increased from 19.0 to 25.8 gC·m−2·a−1 after restoration. As a result, the restored mangrove had a positive effect on climate warming, with increased GWP from 1276 to 1386 g CO2-eq ·m−2·a−1 from 2008 to 2020. This is mainly due to lower GPP and higher Re by young restored mangroves, large water area as well as low salinity induced strong CH4 emissions. Our results indicate new sights that young restored mangrove with large area of water surface may act as carbon sources. However, the long-term climate and ecosystem benefits due to mangrove restoration should not be ignored in future.

The high-frequency response correction of eddy covariance fluxes – Part 2: An experimental approach for analysing noisy measurements of small fluxes

Abstract. Fluxes measured with the eddy covariance (EC) technique are subject to flux losses at high frequencies (low-pass filtering). If not properly corrected for, these result in systematically biased ecosystem–atmosphere gas exchange estimates. This loss is corrected using the system's transfer function which can be estimated with either theoretical or experimental approaches. In the experimental approach, commonly used for closed-path EC systems, the low-pass filter transfer function (H) can be derived from the comparison of either (i) the measured power spectra of sonic temperature and the target gas mixing ratio or (ii) the cospectra of both entities with vertical wind speed. In this study, we compare the power spectral approach (PSA) and cospectral approach (CSA) in the calculation of H for a range of attenuation levels and signal-to-noise ratios (SNRs). For a systematic analysis, we artificially generate a representative dataset from sonic temperature (T) by attenuating it with a first order filter and contaminating it with white noise, resulting in various combinations of time constants and SNRs. For PSA, we use two methods to account for the noise in the spectra: the first is the one introduced by Ibrom et al. (2007a) (PSAI07), in which the noise and H are fitted in different frequency ranges, and the noise is removed before estimating H. The second is a novel approach that uses the full power spectrum to fit both H and noise simultaneously (PSAA21). For CSA, we use a method utilizing the square root of the H with shifted vertical wind velocity time series via cross-covariance maximization (CSAH,sync). PSAI07 tends to overestimate the time constant when low-pass filtering is low, whilst the new PSAA21 and CSAH,sync successfully estimate the expected time constant regardless of the degree of attenuation and SNR. We further examine the effect of the time constant obtained with the different implementations of PSA and CSA on cumulative fluxes using estimated time constants in frequency response correction. For our example time series, the fluxes corrected using time constants derived by PSAI07 show a bias between 0.1 % and 1.4 %. PSAA21 showed almost no bias, while CSAH,sync showed bias of ±0.4 %. The accuracies of both PSA and CSA methods were not significantly affected by SNR level, instilling confidence in EC flux measurements and data processing in set-ups with low SNR. Overall we show that, when using power spectra for the empirical estimation of parameters of H for closed-path EC systems the new PSAA21 outperforms PSAI07, while when using cospectra the CSAH,sync approach provides accurate results. These findings are independent of the SNR value and attenuation level.

Quantitative Assessment of Agricultural Practices on Farmland Evapotranspiration Using EddyCovariance Method and Numerical Modelling

While low cost eddy covariance (EC) techniques based on the open-path laser analyzers have been widely used, they are not very accurate and are restricted to use in non-rainy days. As an alternative, and relevant to promoting precision agriculture where water availability is proving key, the application of the EC technique based on closed-path QCLAS-EC Analyzer is described, in a study of cabbage farmland evapotranspiration (ET). This study uses the advantages of the closed-path EC method to quantitatively assess the impact of agricultural activities on farmland ET and compared with RZWQM2 (Root Zone Water Quality Model) model. The cumulative ET is shown to have increased by 1.5–3.6 mm over ten-days after planting, and decreased by 3.5–8.1 mm over 10 days, following harvesting. While irrigation contributed to ET, the cumulative ten-day ET increase is between 0.6–2.3 mm which is significantly lower than the effects due to planting and harvesting. The RZWQM2 model was used to quantify the effects of four agricultural practices. Simulation of ET attained R2 and RMSE as 0.79 and 0.013 mm/d, respectively. In addition, the RZWQM2 model successfully simulated groundwater levels, Leaf area index, and crop height (R2 values of 0.71, 0.98 and 0.97, respectively). The RZWQM2 model simulates the effects of planting, harvesting, and irrigation on ET, indicating the same directional changes of magnitude with measured data. The results provide a comprehensive and direct study based on the closed-path EC method and RZWQM2 model to assess the impact of multiple agricultural activities on farmland ET and to improve precision agriculture.

Estimating Herd-Scale Methane Emissions from Cattle in a Feedlot Using Eddy Covariance Measurements and the Carbon Dioxide Tracer Method.

Measurements of methane (CH) emissions from ruminants could provide invaluable data to reduce uncertainties in the global CH budget and to evaluate mitigation strategies to lower greenhouse gas emissions. The main objective of this study was to evaluate a new CO tracer (COT) approach that combined CH and CO atmospheric concentrations with eddy covariance (EC) CO flux measurements to estimate CH emissions from cattle in a feedlot. A closed-path EC system was used to measure CH and CO fluxes from a feedlot in Kansas. The EC flux measurements were scaled from landscape to animal scale using footprint analyses. Emissions of CH from the cattle were also estimated using the COT approach and measured CO and CH concentration, and scaled EC CO fluxes. The CH and CO concentration ratios showed a distinct diel trend with greater values during the daytime. Average monthly CH emission estimates using the COT approach ranged from 72 to 127 g animal d, which was consistent with the values reported in other studies that had similar animal characteristics. The COT method CH emission estimates showed good agreement with scaled CH EC fluxes (slope = 0.9 and = 0.8) for cold and dry months. However, the agreement between the two techniques was significantly reduced (slope = 1.5 and = 0.6) during wet and warm months. On average, the COT method CH emission estimates were 3% greater than the EC CH emissions. Overall, our results suggest that the COT method can be used to estimate enteric feedlot CH emissions.

Error characterization of methane fluxes and budgets derived from a long-term comparison of open- and closed-path eddy covariance systems

Wetlands represent the dominant natural source of methane (CH4) to the atmosphere. Thus, substantial effort has been spent examining the CH4 budgets of global wetlands via continuous ecosystem-scale measurements using the eddy covariance (EC) technique. Robust error characterization for such measurements, however, remains a major challenge. Here, we quantify systematic, random and gap-filling errors and the resulting uncertainty in CH4 fluxes using a 3.5 year time series of simultaneous open- and closed path CH4 flux measurements over a sub-boreal wetland.After correcting for high- and low frequency flux attenuation, the magnitude of systematic frequency response errors were negligible relative to other uncertainties. Based on three different random flux error estimations, we found that errors of the CH4 flux measurement systems were smaller in magnitude than errors associated with the turbulent transport and flux footprint heterogeneity. Errors on individual half-hourly CH4 fluxes were typically 6%–41%, but not normally distributed (leptokurtic), and thus need to be appropriately characterized when fluxes are compared to chamber-derived or modeled CH4 fluxes.Integrated annual fluxes were only moderately sensitive to gap-filling, based on an evaluation of 4 different methods. Calculated budgets agreed on average to within 7% (≤1.5 g−CH4 m−2 yr−1). Marginal distribution sampling using open source code was among the best-performing of all the evaluated gap-filling approaches and it is therefore recommended given its transparency and reproducibility.Overall, estimates of annual CH4 emissions for both EC systems were in excellent agreement (within 0.6 g−CH4 m−2 yr−1) and averaged 18 g−CH4 m−2 yr−1. Total uncertainties on the annual fluxes were larger than the uncertainty of the flux measurement systems and estimated between 7–17%. Identifying trends and differences among sites or site years requires that the observed variability exceeds these uncertainties.

Dried, closed-path eddy covariance method for measuring carbon dioxide flux over sea ice

Abstract. The Arctic marine environment plays an important role in the global carbon cycle. However, there remain large uncertainties in how sea ice affects air–sea fluxes of carbon dioxide (CO2), partially due to disagreement between the two main methods (enclosure and eddy covariance) for measuring CO2 flux (FCO2). The enclosure method has appeared to produce more credible FCO2 than eddy covariance (EC), but is not suited for collecting long-term, ecosystem-scale flux datasets in such remote regions. Here we describe the design and performance of an EC system to measure FCO2 over landfast sea ice that addresses the shortcomings of previous EC systems. The system was installed on a 10 m tower on Qikirtaarjuk Island – a small rock outcrop in Dease Strait located roughly 35 km west of Cambridge Bay, Nunavut, in the Canadian Arctic Archipelago. The system incorporates recent developments in the field of air–sea gas exchange by measuring atmospheric CO2 using a closed-path infrared gas analyzer (IRGA) with a dried sample airstream, thus avoiding the known water vapor issues associated with using open-path IRGAs in low-flux environments. A description of the methods and the results from 4 months of continuous flux measurements from May through August 2017 are presented, highlighting the winter to summer transition from ice cover to open water. We show that the dried, closed-path EC system greatly reduces the magnitude of measured FCO2 compared to simultaneous open-path EC measurements, and for the first time reconciles EC and enclosure flux measurements over sea ice. This novel EC installation is capable of operating year-round on solar and wind power, and therefore promises to deliver new insights into the magnitude of CO2 fluxes and their driving processes through the annual sea ice cycle.

Comparing methane emissions estimated using a backward-Lagrangian stochastic model and the eddy covariance technique in a beef cattle feedlot

Accurate methodologies to measure emissions of greenhouse gases (GHG) from livestock systems are necessary to improve the emission coefficients used in national GHG inventories and to evaluate mitigation strategies. The objective of this study was to compare methane (CH4) emissions estimated using the eddy covariance (EC) technique and a backward-Lagrangian stochastic (bLS) model. A closed-path EC system was used to measure CH4 fluxes in a commercial beef cattle feedlot. The EC fluxes were scaled from the feedlot to the animal scale using a footprint analysis. The EC measurements of CH4 concentration and wind data were used with the bLS model to infer CH4 emissions. The average CH4 emissions (±standard deviation) during the experiment were 87 (±30) g animal−1 d−1 and 85 (± 27) g animal−1 d−1 for EC and bLS techniques, respectively. These values are consistent with the results from previous studies with similar animal and feed characteristics. Both techniques were able to capture a pronounced daytime and nighttime variation in CH4 emissions, with higher CH4 emissions during the day and lower emissions at night. Our results indicate that the eddy covariance technique combined with footprint models can be successfully used to accurately measure enteric CH4 from cattle.

Estimating methane emissions from beef cattle in a feedlot using the eddy covariance technique and footprint analysis

Measurements of methane (CH4) emissions from cattle could provide invaluable data to reduce uncertainties in the global CH4 budget and to evaluate mitigation strategies to lower greenhouse gas emissions. The eddy covariance (EC) technique has recently been applied as an alternative to measure CH4 emissions from livestock systems, but heterogeneities in the source area and fetch limitations impose challenges to EC measurements. The main objective of this study was to estimate CH4 emissions rates per pen surface (Fpens) and per animal (Fanimal) from a beef cattle feedlot using the EC technique combined with two footprint models: an analytical footprint model (KM01) and a parametrization of a Lagrangian dispersion model (FFP). Fluxes of CH4 were measured using a closed-path EC system in a commercial feedlot. The footprint models were used to investigate fetch requirements and to estimate Fpens and Fanimal. The aggregated footprint area predicted by KM01 was 5–6 times larger than FFP estimates. On average, Fpens was 8 (FFP) to 14% (KM01) higher than the raw EC flux, but differences between Fpens and EC flux varied substantially depending on the location and size of the flux footprint. The monthly average Fanimal, calculated using Fpens and the footprint weighed stocking density, ranged from 83 to 125ganimal−1d−1 (KM01) and 75–114ganimal−1d−1 (FFP). The emission values are consistent with the results from previous studies in feedlots. These results suggest that the EC technique can be combined with footprint analysis to estimate gas emissions from livestock systems.

An eddy-covariance system with an innovative vortex intake for measuring carbon dioxide and water fluxes of ecosystems

Abstract. Closed-path eddy-covariance (EC) systems are used to monitor exchanges of trace gases (e.g., carbon dioxide [CO2], water vapor [H2O], nitrous oxide and methane) between the atmosphere and biosphere. Traditional EC-intake systems are equipped with inline filters to prevent airborne dust particulate from contaminating the optical windows of the sample cell which causes measurement degradation. The inline filter should have a fine pore size (1 to 20 µm is common) to adequately protect the optics and a large filtration surface area to extend the time before it clogs. However, the filter must also have minimal internal volume to preserve good frequency response. This paper reports test results of the field performance of an EC system (EC155, Campbell Scientific, Inc., Logan Utah, USA) with a prototype vortex intake replacing the inline filter of a traditional EC system. The vortex-intake design is based on fluid dynamics theory. An air sample is drawn into the vortex chamber, where it spins in a vortex flow. The initially homogenous flow is separated when particle momentum forces heavier particles to the periphery of the chamber, leaving a much cleaner airstream at the center. Clean air (75 % of total flow) is drawn from the center of the vortex chamber, through a tube, to the sample cell where it is exposed to the optical windows of the gas analyzer. The remaining 25 % of the flow carries the heavier dust particles away through a separate bypass tube. An EC155 system measured CO2 and H2O fluxes in two urban-forest ecosystems in the megalopolis of Beijing, China. These sites present a challenge for EC measurements because of the generally poor air quality which has high concentrations of suspended particulate. The closed-path EC system with vortex intake significantly reduced maintenance requirements by preserving optical signal strength and sample-cell pressure within acceptable ranges for much longer periods. The system with vortex intake also maintained an excellent frequency response. For example, at the Badaling site, the amount of system downtime attributed solely to clogged filters was reduced from 26 % with traditional inline filters to 0 % with the prototype vortex intake. The use of a vortex intake could extend the geographical applicability of the EC technique in ecology and allow investigators to acquire more accurate and continuous measurements of trace-gas fluxes in a wider range of ecosystems.

Measurements of methane emissions from a beef cattle feedlot using the eddy covariance technique

The eddy covariance (EC) technique has been extensively used in several sites around the world to measure energy fluxes and CO2 exchange at the ecosystem scale. Recent advances in optical sensors have allowed the use of the EC approach to measure other trace gases (e.g. CH4, NH3 and N2O), which has expanded the use of eddy covariance for other applications, including measuring gas emissions from livestock production systems. The main objectives of this study were to assess the performance of a closed-path EC system for measuring CH4, CO2, and H2O fluxes in a beef cattle feedlot and to investigate the spatial variability of eddy covariance fluxes measured above the surface of a feedlot using an analytical flux footprint analysis. A closed-path EC system was used to measure CH4, CO2, and H2O fluxes. To evaluate the performance of this closed-path system, an open-path EC system was also deployed on the flux tower to measure CO2 and H2O exchange. The performance assessment of the closed-path EC system showed that this system was suitable for EC measurements. The frequency attenuations, observed for the closed-path system CO2 and CH4 cospectra in this study, are in agreement with results from previous instrument comparison studies. For the water vapor closed-path cospectra, larger attenuations were likely caused by water vapor molecule interaction with the sampling tube walls. Values of R2 for the relationship between H2O and CO2 fluxes, measured by open-path and closed-path systems, were 0.94–0.98, respectively. The closed-path EC system overestimated the CO2 by approximately 5% and underestimated the latent heat fluxes by about 10% when compared with the open-path system measurements. Measured CH4 and CO2 fluxes during the study period from the feedlot averaged 2.63μmolm−2s−1 and 103.8μmolm−2s−1, respectively. Flux values were quite variable during the field experiment and the footprint analysis was useful to interpret flux temporal and spatial variation. This study shows indication that consideration of atmospheric stability condition, wind direction and animal movement are important to improve estimates of CH4 emissions per pen surface or per head of cattle.

Sensitivity of the annual net ecosystem exchange to the cospectral model used for high frequency loss corrections at a grazed grassland site

Given the increasing use of the eddy covariance technique to estimate CO2 fluxes, more attention needs to be paid to the measurement method used. Among other procedures, the way high frequency loss corrections are established and, more particularly, the choice of the cospectrum shape that is used to implement the correction appears particularly important in this regard. In this study, we compared three approaches to high frequency loss correction for CO2 fluxes measured by a closed path eddy covariance system and evaluated their impact on the carbon balance at the Dorinne Terrestrial Observatory (DTO), an intensively grazed grassland site in Belgium. In the first approach, the computation of correction factors was based on the local cospectra, whereas the other two were based on Kansas cospectra models. The correction approaches were validated by comparing the nighttime eddy covariance CO2 fluxes corrected with each approach and chamber-based total ecosystem respiration estimates. We found that the local cospectra differed from the Kansas cospectra shape, although the site could not be considered as difficult (i.e., fairly flat, homogeneous, low vegetation, sufficient measurement height). The Kansas cospectra have more spectral power at high frequencies than the local cospectra under (un) stable conditions. This difference greatly affected the correction factor, especially for night fluxes. Night fluxes measured by eddy covariance were found to be in good accord with total chamber based ecosystem respiration estimates when corrected with local cospectra and to be overestimated when corrected with Kansas cospectra. As the difference between correction factors was larger in stable than unstable conditions, it acts as a selective systematic error and has an important impact on annual carbon fluxes. On the basis of a 4-year average, at DTO the errors reach 71–150gCm−2y−1 for net ecosystem exchange (NEE), 280–562gCm−2y−1 for total ecosystem respiration (TER) and 209–412gCm−2y−1 for gross primary productivity (GPP), depending on the approach used. We finally encourage site PIs to check the cospectrum shape at their sites and, if necessary, compute frequency correction factors on the basis of local cospectra rather than on Kansas cospectra.

Automated Underway Eddy Covariance System for Air–Sea Momentum, Heat, and CO2 Fluxes in the Southern Ocean

AbstractA ruggedized closed-path eddy covariance (EC) system was designed for unattended direct measurements of air–sea momentum, heat, and CO2 flux, and was deployed on the Research Vessel Icebreaker (RV/IB) Nathaniel B. Palmer (NBP), an Antarctic research and supply vessel. The system operated for nine cruises during 18 months from January 2013 to June 2014 in the Southern Ocean and coastal Antarctica, sampling a wide variety of wind, wave, biological productivity, and ice conditions. The methods are described and the results are shown for two cruises chosen for their latitudinal range, inclusion of both open water and sea ice cover, and relatively large air–water CO2 concentration differences (ΔpCO2). Ship flow distortion was addressed by comparing mean winds, fluxes, and cospectra from an array of 3D anemometers at the NBP bow, comparing measured fluxes with bulk formulas, and implementing and evaluating several recently published data processing techniques. Quality-controlled momentum, heat, and CO2 flux data were obtained for 25% of the periods when NBP was at sea, with most (86%) of the rejected periods due to wind directions relative to the ship >±30° from the bow. In contrast to previous studies, no bias was apparent in measured CO2 fluxes for low |ΔpCO2|. The relationship between momentum flux and wind speed showed a clear dependence on the degree of sea ice cover, a result facilitated by the geographical coverage possible with a ship-based approach. These results indicate that ship-based unattended EC in high latitudes is feasible, and recommendations for deployments of underway systems in such environments are provided.

Comparative measurements of water vapor fluxes over a tall forest using open- and closed-path eddy covariance system

Abstract. Eddy covariance using infrared gas analyzes has been a useful tool for gas exchange measurements between soil, vegetation and the atmosphere. So far, comparisons between the open- and closed-path eddy covariance (CP) system have been extensively made on CO2 flux estimations, while lacking in the comparison of water vapor flux estimations. In this study, the specific performance of water vapor flux measurements of an open-path eddy covariance (OP) system was compared against a CP system over a tall temperate forest in northeastern China. The results show that the fluxes from the OP system (LEop) were generally greater than the LEcp though the two systems shared one sonic anemometer. The tube delay of closed-path analyzer depended on relative humidity, and the fixed median time lag contributed to a significant underestimation of LEcp between the forest and atmosphere, while slight systematic overestimation was also found for covariance maximization method with single broad time lag search window. After the optimized time lag compensation was made, the average difference between the 30 min LEop and LEcp was generally within 6.0 %. Integrated over the annual cycle, the CP system yielded a 5.1 % underestimation of forest evapotranspiration as compared to the OP system measurements (493 vs. 469 mm yr−1). This study indicates the importance to estimate the sampling tube delay accurately for water vapor flux calculations with closed-path analyzers, and it also suggests that some of the imbalance of the surface energy budget in flux sites is possibly caused by the systematic underestimation of water vapor fluxes measured with closed-path eddy covariance systems.